Series of annual, monthly and seasonal precipitation from 50 stations, distributed all over the Basilicata territory (southern Italy), were studied for the period 1923-2000. All the series were checked for homogeneity using MASH v. 1.0.1 software and the time series analysis was performed with the Mann-Kendall nonparametric test in order to detect possible trends. The results show that the annual total rainfall decreased by about 156 mm during the period investigated; the decrease becomes stronger in the last 30 years. There are considerably different trends for the different seasons. In particular, only the winter trend, which is downward, is statistically significant. In this season the total rainfall has decreased by about 133 mm. For this same period the standardized precipitation index (SPI) for multiple time scales of 12, 24 and 48 months has been computed. It appears that periods of drought have been quite frequent starting from 1975, with SPI ranging from about −1 to about −3.

Agricultural terraces represent one of the best ways to prevent land degradation in hilly and mountainous landscapes. However, it is widely recognized that terraced slopes are threatened by agricultural land abandonment. In the literature, very few studies have quantitatively examined the influence of agricultural abandonment on the stability of terraced slopes. The goal of this research is to investigate the relationships between landslide magnitude and land use conditions of agricultural terraced slopes. In particular, Light Detection And Ranging (LiDAR) elevation data, coupled with aerial photo interpretation, were used for the computation of shallow landslide mobilized volumes on terraced slopes affected by an intense rainfall event. We performed the analysis within the Vernazza basin, a small Mediterranean coastal catchment located in the “Cinque Terre” area (Liguria, northwestern Italy), comparing pre‐event and post‐event LiDAR datasets. The results revealed that abandoned terraced slopes have been affected by a higher amount of mobilized debris volumes than still‐cultivated terraces. Furthermore, terraces abandoned for a short time (less than 25–30 years) resulted in the most hazardous land use class, showing erosion rates that were approximately 2 and 3 times higher than terraced slopes abandoned a long time ago (more than 25–30 years) and still‐cultivated terraces, respectively. These findings highlight that land abandonment and agricultural mismanagement can intensify the magnitude of rainfall‐induced shallow landslides. Copyright © 2016 John Wiley & Sons, Ltd.

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Accurate flood mapping is important for both planning activity during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this work, a Bayesian Network (BN) is proposed to integrate remotely sensed data, such as multi-temporal SAR intensity images and InSAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%

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Changes in precipitation extremes for the Basilicata region, southern Italy, have been analyzed using data from 55 precipitation stations with complete daily time series during the period 1951-2010. All the series were submitted to quality control assessment and homogenization. To detect possible trends the time series analysis was performed with the Mann-Kendall non-parametric test. The annual and seasonal total precipitation underwent a general downward trend over the period 1951-2010 mainly due to the autumn-winter decrease of precipitation, although the tendency for the last decade is clearly positive. The precipitation intensity shows a general positive trend, mainly due to the upward trend of spring. The dry spell mean has increased throughout the region over 1951-2010, even if a really important opposite trend characterizes the last decade. The wet spell mean has decreased throughout the region from 1951 to 2010, although a strong inversion of tendency has been recorded in the last 10 years. Trends in the extreme daily precipitation have indicated a general downward tendency, mainly during the summer season. The analysis of multi-day sequences of moderate to heavy rainfall has indicated a corresponding increase in their frequency and intensity, especially in the last decade. The overall results indicate a present hydroclimatic regime characterized by an increase in total rainfall and precipitation intensity and a small decrease in dry spell lengths. The positive change in precipitation magnitude is due to multi-day extreme precipitation rather than to single-day precipitation. This last observation is very important for its huge hydrological impact on the environment. In Basilicata, the increase in intensity/frequency of multi-days extreme events has led to the growth of severe flooding and landsliding events, not only in autumn and winter, but even in the early spring.

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